Senior/Staff Machine Learning Engineer, Zoox

• 2+ years of prior experience as a Technical Lead
• 5+ years of experience developing ML models in Python with PyTorch or TensorFlow
• Industry experience applying ML to sensor data (lidar, radar, and/or cameras)
• Solid understanding of customizing, tuning, and validating ML training pipelines
• You do not need to match every listed expectation to apply for this position

Desirable

• The Zoox 3D Sensor Simulation team’s work is at the core of creating in-the-loop simulation and high fidelity synthetic data for training and testing autonomous vehicle AI
• We are looking for a machine learning professional with experience applying ML to sensor data, such as LiDAR, radar, and cameras
• This role lies at the intersection of machine learning and 3D simulation at Zoox, ranging from learned sensor models to neural 3D reconstruction
• By improving the realism of simulated sensors (lidar, radar, and cameras), you’ll enable the Zoox robotics autonomy stack to learn, improve, and enhance the mobility of humans
• Design, train, and validate ML models that improve the realism of simulated lidar, radar, and camera data in autonomous vehicle (AV) simulation pipelines
• Collaborate with Synthetic Data and HIL Sim teams to integrate 3DGS and NeRF-based 3D reconstruction with simulation of all sensor modalities
• Build and curate training datasets from real and simulated sensor data, including GenAI-based data augmentation
• Partner with Sim V&V and Perception engineers to define sensor realism metrics and close the sim-to-real gaps with the greatest impact on autonomy
• Mentor engineers and interns, and establish best practices for training and deploying ML on Zoox sensor data